1,720,970 research outputs found
Le assicurazioni della salute: inquadramento sistematico e funzione sociale
No full textMuovendo dall’esame delle relazioni tra diritto alla salute e mercato assicurativo, la tesi si incentra sull’analisi delle c.dd. assicurazioni della salute, categoria nella quale vengono ricondotte le assicurazioni contro gli infortuni e/o le malattie, l’assicurazione per il rischio di non autosufficienza ed altre coperture sanitarie di lunga durata, nonché l’assicurazione di spese mediche. Individuati i tratti caratteristici delle suddette figure, l’indagine si sofferma sulla collocazione delle stesse nella sistematica assicurativa, al preminente scopo di individuarne la disciplina applicabile, prefigurando la possibilità di addivenire ad un inquadramento delle medesime differente rispetto a quello prospettato dalla giurisprudenza dominante; ciò, peraltro, senza trascurare le significative interferenze di siffatte coperture con il sistema della responsabilità civile e della sicurezza sociale. La trattazione successiva è dedicata alla funzione sociale delle assicurazioni della salute, soprattutto nell’odierno contesto di crisi dello Stato sociale e nell’ambito della transizione sostenibile in atto. In quest’ultima prospettiva, si pone in luce come il mercato assicurativo della salute possa essere più inclusivo per l’utente, tanto sul piano soggettivo, tramite un ampliamento della platea dei destinatari dell’offerta assicurativa sanitaria, quanto sul piano oggettivo, verificando il rischio effettivamente coperto nelle polizze attualmente diffuse sul mercato e valutando l’opportunità di una sua estensione.Starting with an examination of the relationship between the right to health and the insurance market, the thesis focuses on the analysis of what is referred to as health insurance, a category that includes insurance against accidents and/or illnesses, insurance against the risk of non-self-sufficiency and other long-term health coverage, as well as insurance for medical expenses. Having identified the characteristic features of the above-mentioned forms of insurance, the study focuses on their place in the insurance system, with the primary purpose of identifying the applicable regulations, and considering the possibility of a different classification from the one established by prevailing case law. This is done without neglecting the significant interaction between such coverage and the civil liability and social security systems. The following discussion focuses on the social function of health insurance, especially in today’s context of the crisis of the welfare state and the ongoing transition towards sustainability. In this latter perspective, it highlights how the health insurance market can be more inclusive for the user, both on a subjective level, by expanding the pool of beneficiaries of health insurance offerings, and on an objective level, by assessing the risks actually covered by policies currently available on the market and evaluating the possibility of extending them
Truncated minimal-norm Gauss-Newton method applied to the inversion of FDEM data
Get PDFElectromagnetic induction techniques are among the most
popular methods for non-invasive investigation of the soil. The collection of data is allowed by frequency domain electromagnetic devices. Starting from these data, the reconstruction of some soil properties is a challenging task, as the inverse problem is ill-posed, meaning that the problem is underdetermined, ill-conditioned, that is, the solution is sensitive to the presence of noise in the data, and nonlinear. Iterative procedures are commonly used to solve nonlinear inverse problems and the Gauss–Newton method is one of the most popular. When the problem is ill-conditioned, the Gauss–Newton method is coupled with regularization techniques, to transform the problem into a well-conditioned one. In this
paper, we propose a minimal-norm regularized solution method based on the Gauss–Newton iteration to invert FDEM data. Some numerical examples on synthetic data, regarding the reconstruction of a vertical portion of the soil, show good performances
The minimal-norm Gauss-Newton method and some of its regularized variants. ETNA - Electronic Transactions on Numerical Analysis
Get PDFNonlinear least-squares problems appear in many real-world applications. When a nonlinear model is used to reproduce the behavior of a physical system, the unknown parameters of the model can be estimated by fitting experimental observations by a least-squares approach. It is common to solve such problems by Newton's method or one of its variants such as the Gauss-Newton algorithm. In this paper, we study the computation of the minimal-norm solution to a nonlinear least-squares problem, as well as the case where the solution minimizes a suitable semi-norm. Since many important applications lead to severely ill-conditioned least-squares problems, we also consider some regularization techniques for their solution. Numerical experiments, both artificial and derived from an application in applied geophysics, illustrate the performance of the different approaches
Linear response equations revisited: a simple and efficient iterative algorithm
Get PDFWe present an algorithm to solve the linear response equations for Hartree-Fock, Density Functional Theory, and the Multiconfigurational Self-Consistent Field method that is both simple and efficient. The algorithm makes use of the well-established symmetric and antisymmetric combinations of trial vectors but further orthogonalizes them with respect to the scalar product induced by the response matrix. This leads to a standard, symmetric block eigenvalue problem in the expansion subspace that can be solved by diagonalizing a symmetric, positive definite matrix half the size of the expansion space. Numerical tests showed that the algorithm is robust and stable
Identifying a conductive sphere by time-domain electromagnetic data via Prony-like methods
No full textMinimal-Norm Solution of an Overdetermined System of First Kind Integral Equations: Algorithms and Applications
No full textRegularized minimal-norm solution of an overdetermined system of first kind integral equations
Get PDFOverdetermined systems of first kind integral equations appear in many
applications. When the right-hand side is discretized, the resulting
finite-data problem is ill-posed and admits infinitely many solutions. We
propose a numerical method to compute the minimal-norm solution in the presence
of boundary constraints. The algorithm stems from the Riesz representation
theorem and operates in a reproducing kernel Hilbert space. Since the resulting
linear system is strongly ill-conditioned, we construct a regularization method
depending on a discrete parameter. It is based on the expansion of the
minimal-norm solution in terms of the singular functions of the integral
operator defining the problem. Two estimation techniques are tested for the
automatic determination of the regularization parameter, namely, the
discrepancy principle and the L-curve method. Numerical results concerning two
artificial test problems demonstrate the excellent performance of the proposed
method. Finally, a particular model typical of geophysical applications, which
reproduces the readings of a frequency domain electromagnetic induction device,
is investigated. The results show that the new method is extremely effective
when the sought solution is smooth, but gives significant information on the
solution even for non-smooth solutions
A TWO-DIMENSIONAL INTEGRAL MODEL OF THE FIRST-KIND FOR LIN ELECTROMAGNETIC DATA INVERSION
Get PDFIn this paper we introduce a two-dimensional first-kind integral model to describe the interaction between the soil and an electromagnetic device. This model is used to reconstruct the electrical conductivity of the
soil from electromagnetic data. The definition of the two-dimensional model is derived, and a numerical study of the forward model based on Gauss–Legendre quadrature formulae is presented. To solve the inverse problem, a linear
system obtained from the discretization of the integral equation in the model is considered. The main difficulty is the
severe ill-conditioning of the system, so the Tikhonov regularization method is applied and different regularization matrices and choice-rules for the regularization parameter are proposed. Several numerical tests show the effectiveness of the proposed approach
An Alternating Direction Multiplier Method for the Inversion of FDEM Data
Get PDFIn this paper, we focus on the numerical solution of nonlinear inverse problems in applied geophysics. Our aim is to reconstruct the structure of the soil, i.e., either its electrical conductivity or the magnetic permeability distribution, by inverting frequency domain electromagnetic data. This is a very challenging task since the problem is nonlinear and severely ill-conditioned. To solve the nonlinear inverse problem, we propose an alternating direction multiplier method (ADMM), we prove its convergence, and propose an automated strategy to determine the parameters involved. Moreover, we present two heuristic variations of the ADMM that either improve the accuracy of the computed solutions or lower the computational cost. The effectiveness of the different proposed methods is illustrated through few numerical examples
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